The article, Gartner: Business intelligence ROI, value a matter of mind over money, begins with "Determining the return on investment (ROI) and value of a business intelligence (BI) software investment is often an exasperating task, but not an impossible one, according to one Gartner analyst."
I completely agree, but I also feel it's a matter of maturity, and mature BI environments can get there. I also believe it's a best practice to measure and that it has a high correlation to overall "success", whether success is defined by the numbers or otherwise.
Following are some focuses, in order from healthiest to unhealthiest, that business intelligence programs fall into. As we progress through the focuses, you will notice the focus gets further and further away from the user.
Business Focus #1: Return on Investment
ROI is the holy grail of focus for business intelligence. Those teams that focus on achieving it have learned what business intelligence is all about. Studies have shown that driving toward ROI highly correlates to self-reported program success scores. The focus on ROI just seems to encourage the development team to work backwards to doing the right things day in and day out for the ultimate arbiter of success - the bottom line. Ultimately, to claim this focus, a team must have a great handle on the succeeding focuses well.
Business Focus #2: Data Usage
Those programs that don't measure ROI or are too removed from business processes that drive ROI but still want a business-focused BI program focus on the usage of the data. The objective here is increasing numbers and complexity of usage. With this focus, user statistics such as logins and query bands are tracked; however, little is understood about what the users ultimately do with the results.
Business Focus #3: Data Gathering and Availability
Under this focus, the business intelligence team becomes an internal data brokerage, serving up data for the organization's consumption. Users are not tracked because success is measured in the availability of the data.
In these environments so removed from usage, it is often a struggle for the users to leverage the data. It is not unusual to find a host of downstream processes (i.e., Excel, Access) operating to "fix," "clean" and make this data usable. Users may have grass roots efforts underway to utilize each other's "code."
These environments often come about when there is high complexity in the data extraction and movement layer of the architecture. While it's an accomplishment to deliver the data in these environments, the team should not neglect the need to deliver business intelligence, which requires the accoutrements related to usage to be in place -- such as governance, stewardship and a public relations program.
User satisfaction with such programs begins to fade once they are left to deal with the limitations of delivered raw data.
Technical Focus #1: Key (Technical) Performance Indicators
This is the technical counterpart to a business focus on data usage, but it is not as effective overall. There can be an especially large number of KPIs for the business intelligence program in the area of ETL. These are analogous to the metrics you might place in the operational meta data -- up time, cycle end times, successful loads, clean data levels, etc. While important, they do not comprise the end game.
Technical Focus #2: Adherence to a Guru Approach
One of the ultimate disservices business intelligence teams can do is to spend their budget primarily making sure the architecture adheres to a book standard - as opposed to what works for the users.
Technorati tags: data warehouse, business-intelligence, information management
Posted April 7, 2008 1:15 PM
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